The Race to Locate Twitter Users

Few Twitter users broadcast their location. But businesses and researchers are hunting for ways to infer it.

IBM researcher Jalal Mahmud and colleagues created software that can often identify a Twitter user’s home city, based on the user’s 200 most-recent tweets, according to a recent paper. The researchers looked at the times when a user tweets most frequently – which can indicate the user’s time zone – as well as mentions of sports teams and unique place names.

Mahmud says his model can predict a Twitter user’s home city among the 100 largest U.S. cities within a second with 70% accuracy. Outside those cities, the accuracy declines. His team has filed a patent application for the algorithm.

Researchers say fewer than 3% of Twitter users enable a “geo-tagging” feature that allows app developers to see the latitude and longitude of their tweets. About 30% of users list a location in their Twitter bios, but others list false or fictional locations, such as “in Justin Bieber’s heart.”

Twitter itself has more details on where users are. As long as a user activates the location feature on a smartphone, each tweet is marked with the phone’s location. Twitter uses this and other information to offer geo-targeted ads to areas as small as a zip code; it delivers the ad to users without disclosing their identities to the advertiser.

But Twitter doesn’t share this location data with outsiders, leaving businesses and other groups that want to locate Twitter users largely on their own.

Businesses may want to locate Twitter users to analyze regional differences in sentiment. During a natural disaster, relief organizations have tried to pinpoint flooding to a specific city block.

Gnip, which has contracts to analyze Twitter data, offers “geo-enrichment” services. Gnip also analyzes the content of the tweets – mentions of an unusual street name or a specific restaurant. It works with Esri, a mapping company, to create maps. During Hurricane Sandy, Esri helped the Red Cross FEMA and utilities track the path of the storm using Twitter data.

Inferring people’s locations without their permission can raise privacy concerns. Brent Hecht, a computer science and engineering professor at the University of Minnesota, says seemingly innocuous pieces of information can be tied together in ways that end up revealing something more sensitive. These worries grow as Americans provide more companies with geostamped data from their connected cars, devices, and homes.

In the paper, IBM’s Mahmud wrote that users may be able to avoid being located by censoring themselves on Twitter, “being careful not to mention location names in their tweets,” for example.